correlationMethExprs: Computes the correlation between methylation and expression

Description Usage Arguments Details Value

View source: R/correlationMethExprs.R

Description

Estimates the correlation between methylation and expression. When there are known variables that affect methylation and/or expression, their effect can be substracted using a linear model and then the residuals are used.

Usage

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correlationMethExprs(
  multiset,
  meth_set_name = NULL,
  exprs_set_name = NULL,
  vars_meth = NULL,
  vars_exprs = NULL,
  sel_cpgs,
  flank = 250000,
  betas = TRUE,
  num_cores = 1,
  verbose = TRUE
)

Arguments

multiset

MultiDataSet containing a methylation and an expression slots.

meth_set_name

Character vector with the name of the MultiDataSet's slot containing methylation data.

exprs_set_name

Character vector with the name of the MultiDataSet's slot containing expression data.

vars_meth

Character vector with the names of the variables that will be used to obtain the methylation residuals. By default, none is used and residuals are not computed.

vars_exprs

Character vector with the names of the variables that will be used to obtain the expression residuals. By default, none is used and residuals are not computed.

sel_cpgs

Character vector with the name of the CpGs used in the analysis. If empty, all the CpGs of the methylation set will be used.

flank

Numeric with the number of pair bases used to define the cpg-expression probe pairs.

betas

If set is a GenomicRatioSet, should beta values be used? (Default: TRUE)

num_cores

Numeric with the number of cores to be used.

verbose

Logical value. If TRUE, it writes out some messages indicating progress. If FALSE nothing should be printed.

Details

For each cpg, a range is defined by the position of the cpg plus the flank parameter (upstream and downstream). Only those expression probes that are entirely in this range will be selected. For these reason, it is required that the ExpressionSet contains a featureData with the chromosome and the starting and ending positions of the probes.

Value

Data.frame with the results of the linear regression:


MEAL documentation built on Feb. 3, 2021, 2 a.m.